/*************************************************************************/
/*									 */
/*	Soften thresholds for continuous attributes			 */
/*	-------------------------------------------			 */
/*									 */
/*************************************************************************/


#include "defns.i"
#include "types.i"
#include "extern.i"

namespace classifier_test
{

namespace c45r8
{

Boolean *LHSErr,	/*  Does a misclassification occur with this value of an att  */
	*RHSErr;	/*  if the below or above threshold branches are taken  */

ItemNo	*ThreshErrs;	/*  ThreshErrs[i] is the no. of misclassifications if thresh is i  */

float	*CVals;		/*  All values of a continuous attribute  */


#define	Below(v,t)	(v <= t + 1E-6)


/*************************************************************************/
/*									 */
/*  Soften all thresholds for continuous attributes in tree T		 */
/*									 */
/*************************************************************************/


void SoftenThresh(Tree T)
/*  ------------  */
		   
{
	CVals = (float *) calloc(MaxItem+1, sizeof(float));
	LHSErr = (Boolean *) calloc(MaxItem+1, sizeof(Boolean));
	RHSErr = (Boolean *) calloc(MaxItem+1, sizeof(Boolean));
	ThreshErrs = (ItemNo *) calloc(MaxItem+1, sizeof(ItemNo));

	InitialiseWeights();

	ScanTree(T, 0, MaxItem);

	cfree(ThreshErrs);
	cfree(RHSErr);
	cfree(LHSErr);
	cfree(CVals);
}



/*************************************************************************/
/*								  	 */
/*  Calculate upper and lower bounds for each test on a continuous	 */
/*  attribute in tree T, using data items from Fp to Lp			 */
/*								  	 */
/*************************************************************************/


void ScanTree(Tree T, ItemNo Fp, ItemNo Lp)
/*  --------  */
		   
				  
{
	short v;
	float Val, Se, Limit, Lower, Upper;
	ItemNo i, Kp, Ep, LastI, Errors, BaseErrors;
	ClassNo CaseClass, Class1, Class2;
	Boolean LeftThresh=false;
	Description CaseDesc;
	Attribute Att;

	/*  Stop when get to a leaf  */

	if ( ! T->NodeType ) return;

	/*  Group the unknowns together  */

	Kp = Group(0, Fp, Lp, T);

	/*  Soften a threshold for a continuous attribute  */

	Att = T->Tested;

	if ( T->NodeType == ThreshContin )
	{
	printf("\nTest %s <> %g\n", AttName[Att], T->Cut);

	Quicksort(Kp+1, Lp, Att, Swap);

	ForEach(i, Kp+1, Lp)
	{
		/*  See how this item would be classified if its
		value were on each side of the threshold  */

		CaseDesc = Item[i];
		CaseClass = Class(CaseDesc);
		Val = CVal(CaseDesc, Att);
		
		Class1 = Category(CaseDesc, T->Branch[1]);
		Class2 = Category(CaseDesc, T->Branch[2]);

		CVals[i] = Val;
		LHSErr[i] = (Class1 != CaseClass ? 1 : 0);
		RHSErr[i] = (Class2 != CaseClass ? 1 : 0);
	}

	/*  Set Errors to total errors if take above thresh branch,
		and BaseErrors to errors if threshold has original value  */

	Errors = BaseErrors = 0;
	ForEach(i, Kp+1, Lp)
	{
		Errors += RHSErr[i];

		if ( Below(CVals[i], T->Cut) )
		{
		BaseErrors += LHSErr[i];
		}
		else
		{
		BaseErrors += RHSErr[i];
		}
	}

	/*  Calculate standard deviation of the number of errors  */

	Se = sqrt( (BaseErrors+0.5) * (Lp-Kp-BaseErrors+0.5) / (Lp-Kp+1) );
	Limit = BaseErrors + Se;

	Verbosity(1)
	{
		printf("\t\t\tBase errors %d, items %d, se=%.1f\n",
		   BaseErrors, Lp-Kp, Se);
		printf("\n\tVal <=   Errors\t\t+Errors\n");
		printf("\t		 %6d\n", Errors);
	}

	/*  Set ThreshErrs[i] to the no. of errors if the threshold were i  */

	ForEach(i, Kp+1, Lp)
	{
		ThreshErrs[i] = Errors = Errors + LHSErr[i] - RHSErr[i];

		if ( i == Lp || CVals[i] != CVals[i+1] )
		{
		Verbosity(1)
			printf("\t%6g   %6d\t\t%7d\n",
			CVals[i], Errors, Errors - BaseErrors);
		}
	}

	/*  Choose Lower and Upper so that if threshold were set to
		either, the number of items misclassified would be one
		standard deviation above BaseErrors  */

	LastI = Kp+1;
	Lower = Min(T->Cut, CVals[LastI]);
	Upper = Max(T->Cut, CVals[Lp]);
	while ( CVals[LastI+1] == CVals[LastI] ) LastI++;

	while ( LastI < Lp )
	{
		i = LastI + 1;
		while ( i < Lp && CVals[i+1] == CVals[i] ) i++;

		if ( ! LeftThresh &&
		 ThreshErrs[LastI] > Limit &&
		 ThreshErrs[i] <= Limit &&
		 Below(CVals[i], T->Cut) )
		{
		Lower = CVals[i] -
			(CVals[i] - CVals[LastI]) * (Limit - ThreshErrs[i]) /
			(ThreshErrs[LastI] - ThreshErrs[i]);
		LeftThresh = true;
		}
		else
		if ( ThreshErrs[LastI] <= Limit &&
		 ThreshErrs[i] > Limit &&
		 ! Below(CVals[i], T->Cut) )
		{
		Upper = CVals[LastI] +
			(CVals[i] - CVals[LastI]) * (Limit - ThreshErrs[LastI]) /
			(ThreshErrs[i] - ThreshErrs[LastI]);
		if ( Upper < T->Cut ) Upper = T->Cut;
		}

		LastI = i;
	}

	T->Lower = Lower;
	T->Upper = Upper;

	Verbosity(1) printf("\n");

	printf("\tLower = %g, Upper = %g\n", T->Lower, T->Upper);
	}

	/*  Recursively scan each branch  */

	ForEach(v, 1, T->Forks)
	{
	Ep = Group(v, Kp+1, Lp, T);

	if ( Kp < Ep )
	{
		ScanTree(T->Branch[v], Kp+1, Ep);
		Kp = Ep;
	}
	}
}

}

}
